Meteorological application of wind speed and direction linked to remote sensing images for the modelling of sand drift potential and dune morphology

Abstract

Wind velocity and its direction are important erosive factors affecting sand drift potential and dune morphology in arid and semi‐arid environments. The study assesses sand drift potential using wind meteorological data acquired from eight synoptic stations of Kerman province in southeastern Iran for a statistical period of 2006–2010. Three diagrams including wind rose, storm rose and sand rose were plotted for the selected stations using WR Plot View.8 and Sand Rose Graph 3.0. The analyses were performed at seasonal and mean annual time scales. The unidirectional index and wind energy classification were compared with sand dune morphology obtained from satellite images. The seasonal analysis indicated intermediate directional variability and high energy winds, with the most erosive winds occurring in winter. The total sand flux in all directions and discharge sand flow in the resultant drift direction ranged from 53.4 to 319.1 and from 13.8 to 247.6 t·m−1·year−1, respectively. The transverse dune was the main type of sand dune detected in the region with an intermediate directional variability, implying positive sand supplies. Dune morphology coincided reasonably well with the resultant drift direction. An appropriate match was found between the wind data analyses and the morphology of dunes observed in the satellite images.

Hybrid system model for wind abrasion segmentation using semi-automatic classification of remote sensing multispectral areas

“…The direction of erosive winds plays a crucial role in determining the origin and path of sand and dust storms originating from arid and semiarid regions [ 70 ]. Wind speed is a significant factor in the transportation of sand and dust by wind, which can cause erosion, resulting in the formation of sand dunes and ripples [ 71 ]. By expanding the assessment, it is possible to create risk zones applicable to nearby areas.…”

Spatiotemporal analysis of dune stabilization in the Kyzylkum and Karakum sandy deserts

“…The regional sand flow results could be approximated using three methodologies (Pye and Tsoar, 2009): by considering the a) wind velocity data, with a sand transport rate equation, such as that proposed by Bagnold (1941); ; b) sandstorm duration and direction records (Dubief, 1952); and c) size and orientation of aeolian bedforms and sand streaks (Cohen-Zada et al, 2017). The drift potential is assumed to be an essential factor determining the formation and growth of dunes provided sufficient wind records are available (Zamani et al, 2020;Hu et al, 2021), and the first approach (use of wind chronicles) can yield the results for any period and particle size (Pye and Tsoar, 2009). As this is not always the case in remote desert areas, we tested the data sources to identify which method (reanalysis or weather measurements) was more accurate.…”

“…As this is not always the case in remote desert areas, we tested the data sources to identify which method (reanalysis or weather measurements) was more accurate. The DP and sand rose exponents, RDP, RDD, and wind directionality index (UDI = RDP/DP) were calculated using the established MATLAB algorithm, according to and Zamani et al (2020). The data from 36 NOAA weather stations for 1 January 2010, to 31 December 2019, were compared to the nearest grid point of the ERA5 reanalysis assimilated dataset.…”